Dataset Information

Gastric cancers of Western European and African patients

ABSTRACT: Gastric cancer is the second most common cause of cancer death worldwide, but incidence and mortality rates show large variations across different countries. Variation in risk factors between different populations, including environmental and host factors influencing gastric cancer risk, have been reported but little is known about the biological differences between gastric cancers from different geographic locations. We set out to study genomic instability patterns of gastric cancers obtained from patients from United Kingdom (UK) and South Africa (SA). DNA was isolated from 67 gastric adenocarcinomas, 33 UK patients, 9 Caucasian SA patients and 25 native SA patients. Microsatellite instability and chromosomal instability were analyzed by PCR and microarray comparative genomic hybridization, respectively. Data was analyzed by supervised univariate and multivariate analyses as well as unsupervised hierarchical cluster analysis. Tumors from Caucasian and native SA patients showed significantly more microsatellite instable tumors (p<0.05). For the microsatellite stable tumors, geographical origin of the patients correlated with cluster membership, derived from unsupervised hierarchical cluster analysis (p=0.001). Several chromosomal alterations showed significantly different frequencies in tumors from UK patients and native SA patients, but not between UK patients and Caucasian SA patients and between native and Caucasian SA patients. In conclusion, gastric cancers from South African and UK patients show differences in genetic instability patterns, indicating possible different biological mechanisms underlying the disease.

ORGANISM(S): Homo sapiens

PROVIDER: GSE22789 | GEO | 2011/06/28

SECONDARY ACCESSION(S): PRJNA127811

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background Worldwide, gastric cancer is the fourth most common malignancy and the most common cancer in East Asia. Development of targeted therapies for this disease has focused on a few known oncogenes but has had limited effects. Objective To determine oncogenic mechanisms and novel therapeutic targets specific for gastric cancer by identifying commonly dys-regulated genes from the tumors of both Asian-Pacific and Caucasian patients. Design We generated transcriptomic profiles of 22 Caucasian gastric cancer tumors and their matched non-cancerous samples, and performed an integrative analysis across different gastric cancer gene expression datasets. We examined the inhibition of commonly overexpressed oncogenes and their constituent signaling pathways by RNAi and/or pharmacologic inhibition. Results We found that HNF4α upregulation was a key signaling event in gastric tumors from both Caucasian and Asian patients, and HNF4α antagonism was antineoplastic. Perturbation experiments in GC tumor cell lines and xenograft models further demonstrated that HNF4α is downregulated by AMPKα signaling and the AMPK agonist metformin; blockade of HNF4α activity resulted in cyclin downregulation, cell cycle arrest, and tumor growth inhibition. HNF4α also regulated WNT signaling through its target gene WNT5A, a potential prognostic marker of diffuse type gastric tumors. Conclusions Our results indicate that HNF4α is a targetable oncoprotein in gastric cancer, is regulated by AMPK signaling through AMPKα, and resides upstream of WNT signaling. HNF4α may regulate “metabolic switch” characteristic of a general malignant phenotype and its target WNT5A has potential prognostic values. The AMPKα-HNF4α-WNT5A signaling cascade represents a potentially targetable pathway for drug development. Integrative analysis of Caucasian and Asian-Pacific gastric tumor expression datasets (including newly generated transcriptomic profiling of 22 tumors in this study) revealed a relatively small common sets of highly overexpressed genes.

Dataset Information

Gastric cancers of Western European and African patients

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets